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RIS citation export for THXD1: Machine Learning for Improved Accelerator Health and Reliability

TY  - UNPB
AU  - Yucesan, Y.A.
ED  - Biedron, Sandra
ED  - Simakov, Evgenya
ED  - Milton, Stephen
ED  - Anisimov, Petr M.
ED  - Schaa, Volker R.W.
TI  - Machine Learning for Improved Accelerator Health and Reliability
J2  - Proc. of NAPAC2022, Albuquerque, NM, USA, 07-12 August 2022
CY  - Albuquerque, NM, USA
T2  - International Particle Accelerator Conference
T3  - 5
LA  - english
AB  - This talk will summarize the effort by the community in using machine learning for improved accelerator operations. This talk will also discuss efforts to implement a machine learning framework to improve accelerator reliability at the Spallation Neutron Source. It will describe new prognostics algorithms for detecting beam faults, classification of the fault sources, and efforts to integrate the algorithms into operations. it will also describe additional efforts to utilize ML for health and predictive prognostics on critical accelerator hardware and targets.
PB  - JACoW Publishing
CP  - Geneva, Switzerland
ER  -